189 citations · 326 across the 15 of their papers we have counts for
7 papers · 1 filter
Graph and Recurrent Neural Network-based Vehicle Trajectory Prediction For Highway Driving
Xiaoyu Mo, Yang Xing, Chen Lv
Integrating trajectory prediction to the decision-making and planning modules of modular autonomous driving systems is expected to improve the safety and efficiency of self-driving…
Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction
Xiaoyu Mo, Yang Xing, Chen Lv
Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential for the safe and efficient operation of connected automated vehicles under complex d…
Human-in-the-Loop Deep Reinforcement Learning with Application to Autonomous Driving
Jingda Wu, Zhiyu Huang, Chao Huang +4
Due to the limited smartness and abilities of machine intelligence, currently autonomous vehicles are still unable to handle all kinds of situations and completely replace drivers.…
ReCoG: A Deep Learning Framework with Heterogeneous Graph for Interaction-Aware Trajectory Prediction
Xiaoyu Mo, Yang Xing, Chen Lv
Predicting the future trajectory of surrounding vehicles is essential for the navigation of autonomous vehicles in complex real-world driving scenarios. It is challenging as a vehi…
Interaction-Aware Trajectory Prediction of Connected Vehicles using CNN-LSTM Networks
Xiaoyu Mo, Yang Xing, Chen Lv
Predicting the future trajectory of a surrounding vehicle in congested traffic is one of the basic abilities of an autonomous vehicle. In congestion, a vehicle's future movement is…
Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approach
Peng Hang, Chen Lv, Yang Xing +2
Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on roads in the future for a long time, how to merge AVs into human drivers traffic ecology and mi…